Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration
📰 ArXiv cs.AI
Learn to separate refusal from capability in code LLMs via ablation to improve vulnerability detection and code security
Action Steps
- Build a dataset of labeled vulnerable code using existing methods
- Apply instruction-tuning to an LLM to inject specified vulnerabilities
- Configure ablation to separate refusal from capability in code LLMs
- Test the effectiveness of the LLM in detecting vulnerabilities
- Run experiments to evaluate the impact of ablation on vulnerability detection
Who Needs to Know This
Security engineers and researchers on a team benefit from understanding how to evaluate code LLMs' capabilities and limitations, and how to improve vulnerability detection
Key Insight
💡 Ablation can help distinguish between an LLM's refusal to perform a task and its inability to do so, improving vulnerability detection
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🚨 Improve code security by separating refusal from capability in LLMs via ablation 💻
Key Takeaways
Learn to separate refusal from capability in code LLMs via ablation to improve vulnerability detection and code security
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